Abstract: Various embodiments are directed to apparatuses, methods, and computer program products for executing centralized data verification using supported data structures associated with one or more third-party system.

Abstract: An audio stream is detected during a communication session with a user. Natural language processing on the audio stream is performed to update a set of attributes by supplementing the set of attributes based on attributes derived from the audio stream. A set of filter values is updated based on the updated set of attributes. The updated set of filter values is used to query a set of databases to obtain datasets. A probabilistic program is executed during the communication session by determining a set of probability parameters characterizing a probability of an anomaly occurring based on the datasets and the set of attributes. A determination is made if whether the probability satisfies a threshold. In response to a determination that the probability satisfies the threshold, a record is updated to identify the communication session to indicate that the threshold is satisfied.

Abstract: Various methods, apparatuses/systems, and media for data migration readiness of a target data source are disclosed. A processor receives a request having configurable filters and parameters from a consumer service to obtain data; invokes, in response to receiving the request, a service application programming interface (API) for the data; fetches requested data from a legacy data source in response to calling the service API; fetches data corresponding to the same request having the same configurable filters and parameters from a target data source; compare the fetched data from the legacy data source to the fetched data from the target data source; generates, in response to comparing, a data quality validation score; and when it is determined that the data quality validation score is equal to or more that predetermined threshold value, validates the target data source for migration readiness and terminating the legacy data source.

Abstract: A computer-implemented method of integrating decoupled front-end and back-end processes is disclosed. The method comprises receiving a front-end configuration including validation specifications and a back-end configuration including data validation rules; receiving a data item via forms-based interface associated with the front-end configuration, the data item having been validated based on the validation specifications; mapping the data item to a back-end data object; detecting a conflict between the validation specifications and the validation rules; altering a back-end validation process associated with the back-end data object; causing storing the data item in a database system in association with the back-end data object.

Abstract: A service to provide anomaly detection receives a request to back-test the service. The request includes information for accessing a dataset of historical data. The service executes workflows to ingest the data, train a plurality of machine learning models to perform anomaly detection, and detect anomalies in the dataset. A representation of the detect anomalies is generated and presented to a user. The service receives an indication to activate the service to provide ongoing anomaly detection services.

Abstract: A disclosed method for implementing containers in an information handling system generates, with a first non-privileged container, a request that is sent to a RESTful API. Whenever the API identifies a request requiring host access the API launches a second container, which is configured to operate in a privileged execution mode. The second container accesses the host and executes the requested actions. When the request completes, the first container resumes non-privileged execution, thereby confining privileged mode execution to a container that is only active during host interaction. The host access can be access required to: exchange data with the host, query the host for hardware information, and modify host configuration. The host may be implanted within a device featuring an HCI infrastructure. In one configuration, the host resides of one of multiple distinct nodes of an HCI appliance.

Abstract: The sizes of image files for deploying software in a computing environment can be reduced according to some examples described herein. In one example, a system can identify base image files that each include at least a predefined amount of dependencies relied upon by target software. The system can then select a particular base image file, from the base image files, having a smallest size as compared to a remainder of the base image files. The system can then build a customized image file from the base image file, where the customized image file is configured for deploying the target software to a computing environment.

Abstract: Automatic data modeling in a low-latency data access and analysis system includes identifying an analytical-object in response to first data expressing usage intent, generating an analytical model generation data-query for the analytical-object, obtaining a trained analytical model generated in accordance with the analytical model generation query and trained using results data obtained in accordance with the analytical-object, generating a resolved-request representing second data expressing usage intent and indicating a request for results data obtained using the trained analytical model, generating an analytical model results data-query for obtaining the results data in accordance with the trained analytical model and the analytical-object, and outputting data for presenting a visualization of the results data obtained by executing the analytical model results data-query, wherein a first portion of the results data corresponds with the analytical-object and a second portion of the results data corresponds

Abstract: Systems and methods provide a system that gathers information about data as it progresses through data processing pipelines of data analysis projects. The data analytics system derives value indicators and implicit metadata from the data processing pipelines. For example, the data analytics system may derive value indicators and implicit metadata from data-related products themselves, semantic analysis of the code/processing steps used to process the data-related products, the structure of data processing pipelines, and human behavior related to production and usage of data-related products. Once a new data analysis project is initiated, the data analytics system gathers parameters and characteristics about the new data analysis project and references the value indicators and implicit metadata to recommend useful processing steps, datasets, and/or other data-related products for the new data analysis project.

Abstract: A process of fulfilling a database deployment request for a data platform. A compute service manager of the data platform scans one or more accounts of a consumer region of the data platform for a pending listing fulfillment request, where the pending listing request includes a request for deployment of a consumer database and an associated share of grant metadata of the consumer database within the consumer region. When the compute service manager determines that an account of the one or more accounts has a pending listing fulfillment request, the compute service manager determines a listing for the pending listing fulfillment request based on listing data of the account. The compute service manager determines that no other fulfillment task is scheduled for the pending listing fulfillment request and schedules a background fulfillment task to perform the fulfillment process for the pending listing fulfillment request.

Abstract: Methods, systems, and computer-readable storage media for notarized communication between platform systems is provided. A first data object is notarized by storing a first root hash value at a blockchain network. The first root hash value is notarized in response to a transaction request received through a first notarization interface instantiated at a first platform system. A subscription for the first platform system is established to provide notification events in relation to a second data object. The first root hash value comprises an object reference to a second root hash value for the second data object. A notification event is sent for the second data object to the first platform system, comprising a third root hash value of a third data object associated with the second data object. The third data objects is notarized at the blockchain network by the second platform system through a second notarization interface.

Abstract: Distributed pseudo-random subset generation includes obtaining a data-query indicating a first table having a first column including unique values, a second table having a second column including unique values, a join clause joining the first table and the second table on the first column and the second column, and a limit value, pseudo-random filtering the first table to obtain left intermediate data and left filtering criteria, pseudo-random filtering the second table to obtain right intermediate data and right filtering criteria, obtaining intermediate results data by full outer joining the left intermediate data and the right intermediate data, obtaining results data by filtering the intermediate results data using most-restrictive filtering criteria among the left filtering criteria and the right filtering criteria, and outputting the results data, wherein outputting the results data includes limiting the cardinality of rows of the results data to be at most the limit value.

Abstract: One or more computer processors classify each log line in a plurality of unlabeled log lines as an erroneous log line or a non-erroneous log line. The one or more computer processors templatize each classified erroneous log line and non-erroneous log line in the plurality of unlabeled log lines. The one or more computer processors cluster erroneous log templates into erroneous log template clusters and the non-erroneous log templates into non-erroneous log template clusters. The one or more computer processors eliminate the erroneous log template clusters and the non-erroneous log template clusters that exceed a frequency threshold. The one or more computer processors train a log anomaly model utilizing=remaining erroneous log template clusters and remaining non-erroneous log template clusters. The one or more computer processors identify a subsequent log line as anomalous or non-anomalous utilizing the trained log anomaly model.

Abstract: A system and a method for grouping log lines in application log file is presented. The system uses logging framework code instrumentation in order to obtain a relation between the actual log line and the place in source code from which a method responsible for writing the line has been called. As the all information on the relation is stored in external metadata files, the structure of the log files remains unchanged. Using the above mentioned metadata and a raw log file, each log line in the file can be assigned to a group related to the place in source code from which the line has been logged, by the system. Next such a grouped log file can be displayed to the user in order to simplify the analysis of the application behavior.

Abstract: A method for computer estimations based on statistical tree structures involves obtaining a statistical tree structure for reference elements. The statistical tree structure includes leaf nodes segmenting a statistic for a data label according to data features in the reference elements, and intermediate nodes connecting a first node to the leaf nodes. Each of the first node and the intermediate nodes provide a branching based on one of the data features. The method further includes obtaining target data, including values for the data features, and a value for the data label. The method also includes selecting the first node, associated with a first data feature, traversing the statistical tree structure to a leaf node by matching the values of the data features to the branching of the intermediate nodes, and assessing the value for the data label in the target data based on the statistic associated with the leaf node.

Abstract: A method for verifying structured data includes receiving structured data, deconstructing the structured data into corresponding elements and obtaining standard structured data having corresponding standard elements. The method also includes comparing the elements of the structured data with the standard elements of the standard structured data to identify any element differences. For each element difference, the method includes comparing the element difference against a registry of element comparisons, determining whether the element difference is expected or unexpected based on a heuristic or at least one rule, and when the element difference is unexpected, generating a signal indicating the presence of an unexpected element in the structured data.

Abstract: Processing range operation data management statements in a database is provided. The method comprises receiving statements for range operations that specify referenced pages in the database. The range operations are stored in a search structure in a table directory in the database and applied to any referenced pages in a memory buffer pool. Application of the range operations is postponed for any referenced pages not in the memory buffer pool. The database determines if reading the postponed pages into the buffer pool would exceed a specified input/output threshold. If reading the postponed pages into the buffer pool does not exceed the specified threshold, the database reads the postponed pages from disk to the buffer pool asynchronously in parallel, and the range operations are then applied to the postponed pages. Pages modified by the range operations are then written from the buffer pool back to disk.

Abstract: A method for employing a differentiable ranking based graph sparsification (DRGS) network to use supervision signals from downstream tasks to guide graph sparsification is presented. The method includes, in a training phase, generating node representations by neighborhood aggregation operators, generating sparsified subgraphs by top-k neighbor sampling from a learned neighborhood ranking distribution, feeding the sparsified subgraphs to a task, generating a prediction, and collecting a prediction error to update parameters in the generating and feeding steps to minimize an error, and, in a testing phase, generating node representations by neighborhood aggregation operators related to testing data, generating sparsified subgraphs by top-k neighbor sampling from a learned neighborhood ranking distribution related to the testing data, feeding the sparsified subgraphs related to the testing data to a task, and outputting prediction results to a visualization device.

Abstract: A process of fulfilling a database deployment request for a data platform. A compute service manager of the data platform scans one or more accounts of a consumer region of the data platform for a pending listing fulfillment request, where the pending listing request includes a request for deployment of a consumer database and an associated share of grant metadata of the consumer database within the consumer region. When the compute service manager determines that an account of the one or more accounts has a pending listing fulfillment request, the compute service manager determines a listing for the pending listing fulfillment request based on listing data of the account. The compute service manager determines that no other fulfillment task is scheduled for the pending listing fulfillment request and schedules a background fulfillment task to perform the fulfillment process for the pending listing fulfillment request.

Abstract: A method for employing a supervised graph sparsification (SGS) network to use feedback from subsequent graph learning tasks to guide graph sparsification is presented. The method includes, in a training phase, generating sparsified subgraphs by edge sampling from input training graphs following a learned distribution, feeding the sparsified subgraphs to a prediction/classification component, collecting a predication/classification error, and updating parameters of the learned distribution based on a gradient derived from the predication/classification error. The method further includes, in a testing phase, generating sparsified subgraphs by edge sampling from input testing graphs following the learned distribution, feeding the sparsified subgraphs to the prediction/classification component, and outputting prediction/classification results to a visualization device.

Abstract: Systems and methods are described for assigning a processing task from one component of a data intake and query system to a different component of the data intake and query system. As part of processing a query, the system can determine that a particular processing task is to be executed by a particular component of the data intake and query system. Based on the characteristics of the component that is to execute the processing task, the system can assign the task or a supplemental task to one or more other components of the data intake and query system.

Abstract: A blockchain generation system included in each of servers forming a blockchain network includes a blockchain condition setting device that sets a blockchain configuration condition statement based on an operator's input to a screen of a user interface. A data detector detects result data stored in a memory of a programmable logic controller according to an operation of a process equipment based on the blockchain configuration condition statement. A blockchain generator generates blockchain data based on the result data detected from the memory of the programmable logic controller and transmits the blockchain data to a plurality of client servers connected via the blockchain network. A storage device stores the blockchain data and store blockchain data received from the client servers.

Abstract: The present invention relates to an electrothermal converter, which has at least one cold side and one warm side. Provision is made that all the components of the converter cope with the thermal loads appearing when the converter is operated and/or in particular maintains its mechanical stability.

Abstract: Implementations described herein relate to systems and methods to provide platform agnostic query acceleration. In some implementations, a method includes receiving, at a processor associated with a query acceleration service, a request from an client/application, wherein the request conforms to a particular wire protocol of a plurality of supported wire protocols, and wherein the request includes header data and body content data, analyzing the request to identify at least one of a query and a command in the body content data, determining an optimal matched model of the one or more query acceleration models, rewriting the query based on the optimal matched model, transmitting the rewritten query to the query processing platform, receiving a response to the rewritten query or the query from the query processing platform, and transmitting the received response to the application, wherein the transmission is configured based on the particular wire protocol.

Abstract: It is presented a method for enabling allocation of resources for a plurality of hosts. The method is performed by a server (1) and comprises identifying (S100) a service running on one or more of the plurality of hosts, determining (S140) a stretch factor for a recurring load pattern for the service running on the one or more of the plurality of hosts, and storing (S150) the identified service together with the determined stretch factor. It is also presented a server, a computer program and a computer program product.

Abstract: Methods are described herein for creating and installing software updates which may be rolled back, without requiring large processing capabilities and/or large storage capacity at a device. Delta software updates are determined comprising differences, on a bit-level, between a first version of the software and a second, updated, version of the software, and metadata defining how to apply the differences. Methods of performing a rollback-capable update at a device are also described herein.

Abstract: A system is provided that includes a document validation within a non-relational database system that is capable of reviewing documents according to one or more validation rules. The document validator may be incorporated within a non-relational database engine and may perform validation operations when one or more database functions are performed.

Abstract: An example operation may include one or more of creating, by a blockchain user of a blockchain network, a world state checkpoint transaction requesting world state validation, endorsing, by one or more endorser nodes or peers, the world state checkpoint transaction, transferring endorsements to the blockchain user, recording, by an orderer node or peer, the endorsed world state checkpoint transaction into a block, validating and committing all transactions in the block, calculating and signing a hash of a current world state, by all blockchain nodes or peers of the blockchain network, and verifying, by the blockchain user, world state integrity from the calculated and signed hashes of the current world state.

Abstract: Technology is disclosed for recovering the consistency of a RAID (Redundant Array of Independent Disks) metadata database when data corruption is detected in the RAID metadata database. The RAID metadata database includes super sectors, stage sectors, and a data region. Valid data within the data region is a contiguous set of sectors extending from a head sector to a tail sector. In response to data corruption in one of the two super sectors, a set of pointers contained in the other super sector is used to identify the head sector and tail sector. In response to data corruption in both super sectors, the head sector and tail sector are located based on the contents of the sectors in the data region. Techniques are also disclosed for recovering consistency when the data corruption occurs in the stage sectors and/or data region.

Abstract: Techniques and apparatus for dynamic data access mode processes are described. In one embodiment, for example, an apparatus may a processor, at least one memory coupled to the processor, the at least one memory comprising an indication of a database and instructions, the instructions, when executed by the processor, to cause the processor to determine a database utilization value for a database, perform a comparison of the database utilization value to at least one utilization threshold, and set an active data access mode to one of a low-utilization data access mode or a high-utilization data access mode based on the comparison. Other embodiments are described.

Abstract: Scanning and rescanning detect state inconsistencies between data entities in repositories or other components of a distributed computing environment. First, entities are scanned based on a cutoff time TO. Entities for which state comparison is undesired are placed in a skipped entity list. Any inconsistencies found in other entities is reported. Then subsequent rescanning fetches state and attempts to pare down the skipped entity list. Rescanning may be capped. Inconsistencies may be detected without requiring downtime from services that update data entity state, and false reports of inconsistency may be avoided.

Abstract: Described are techniques for code review using Quantitative Linguistics (QL). The techniques include comparing received code to one or more repositories of code and identifying one or more portions of rare code in the received code that satisfy a rarity threshold relative to the one or more repositories of code. The techniques further include generating annotated code by annotating the received code at the one or more portions of rare code and transmitting the annotated code to a testing platform.

Abstract: The invention comprises a decentralized consensus protocol for blockchains in which the computation can be used to search for good approximate solutions to any optimization problem. This protocol allows the wasted energy to be used for finding approximate solutions to problems submitted by any nodes (called clients). This protocol works in a similar way to proof-of-work, and it makes nodes evaluate a large number of solution candidates to add a new block to the chain. A client provides a search program that implements any search algorithm that finds a good solution by evaluating a large number of solution candidates. The node that finds the best approximate solution is rewarded by the client.

Abstract: Various embodiments of the present application set forth a computer-implemented method that includes transmitting, by a wearable device, a first request that includes a first set of parameters, receiving, by the wearable device, a first set of values based on the first set of parameters, wherein the first set of values are provided by a first data source, displaying, by the wearable device, a first dashboard that includes a first visualization associated with the first set of values, determining that a first physical interaction with a first physical input device associated with the wearable device occurred, and in response to the first physical interaction, causing the first visualization to display a first data value included in the first set of values.

Abstract: A central server receives API calls requesting services. The central server identifies whether the API calls are associated with a merchant. A distribution is constructed based on the API calls. The central server further executes a pre-defined rule to identify a set of the API calls belonging to a maximum percentile in the distribution and a set of the API calls belonging to a minimum percentile in the distribution before estimating a set of the anomalous data points with one or more goodness of fit functions against the maximum percentile and the minimum percentile. A GUI receives a critical value from a user. In response to receiving the critical value, the central server generates probabilities of the set of the anomalous data points before displaying a set of the anomalous data points in response to the probabilities being less than the critical value.

Abstract: The subject technology inserts, by a first transaction, a new version of an object, the inserting corresponding to a first statement from the first transaction, the first statement including information indicating a first key, a first transaction identifier, a first statement number, and a first restart count. The subject technology performs, by a second transaction, a range read, the range read including information indicating the first key. The subject technology receives, after performing the range read, a set of conflicting transactions. The subject technology determines that a conflict occurred between the first transaction and a third transaction from the set of conflicting transactions.

Abstract: Storage devices can be configured to desirably reduce the number of times a zone reset or erasure occur via the use of one or more paired overwrite memory blocks. These storage devices can include a plurality of memory devices with some of these memory devices designated as overwrite memory devices. A controller within the storage device can be configured to direct the storage device to generate one or more subsets within the memory devices such as zones, pair each of subsets with at least one or more overwrite memory devices, store data sequentially within the subset of memory devices, and store any received overwrite data in the overwrite memory devices in chronological order. Data stored within the subsets of memory devices are not erased and instead of being overwritten directly, are instead pointed via a control table to a location in the overwrite memory devices storing the corresponding overwrite data.

Abstract: Exemplary methods, apparatuses, and systems include a destination node receiving, from a source node, a hash of data stored by the source node and designated for transfer from the source node to the destination node. In response to determining the hash received from the source node maps to data stored by the destination node, the destination node reads the data into a write buffer and transmits an indication to the source node that the data is present at the source node. The destination node reads the data from write buffer and, in response to determining the data read from the write buffer remains unchanged as stored by the destination node, increases a reference count for the data as stored by the destination node.

Abstract: Techniques for storage management involve: if it is determined that a source storage slice of a file system is to be recycled, identifying, from the source storage slice including a plurality of storage blocks, an orphan storage block that is inaccessible by a client of the file system; replicating data of the orphan storage block to a target storage block, the target storage block being located in a target storage slice within a predetermined isolation area of the file system; and generating second metadata of the target storage block based at least on first metadata of the orphan storage block, the second metadata including at least an identification of the orphan storage block. Therefore, the management performance can be improved, and the storage costs can be reduced.

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: A database command replacer intercepts database commands to one or more database servers, extracts the database command and defined parameters within the command, and determines if the database command is defined in the list of commands subject to replacement; if not, the command is passed through to the destination database server. If the database command is in the list of commands subject to replacement, the replacement command is retrieved, the mapped parameter values are incorporated into the replacement command, the replacement command is transmitted to the destination database server, and the resultant information is relayed back to the origination program. No changes are required to either the client or server software in existing client/server database arrangements.

Abstract: An apparatus includes a processing device comprising a processor coupled to a memory, with the processing device being configured, in conjunction with synchronous replication of at least one logical storage volume between first and second storage systems, to acquire an address lock for a set of pages of the logical storage volume starting from a particular page of the logical storage volume, to determine content-based signatures for respective pages of the set of pages, to compute an additional signature as a function of the content-based signatures, and to send the additional signature and a pointer to the particular page from the first storage system to the second storage system, so as to permit the second storage system to verify consistency of the set of pages in the second storage system relative to the set of pages in the first storage system. Such operations are repeated for other sets of pages.

Abstract: Embodiments of the present disclosure provide a method, device, and computer program product for managing cache. There is provided a method of managing a cache, comprising: receiving a current operation request from a user, data requested by the current operation request being to be duplicated to the cache; obtaining a plurality of historical operation requests of the user, the plurality of historical operation requests being received prior to the current operation request; determining a predicted operation request for the user based on the plurality of historical operation requests and the current operation request; and in accordance with determining that a type of an operation associated with the predicted operation request belongs to predetermined types, adjusting data in the cache based on the predicted operation request.

Abstract: A method for improving consensus in a blockchain network through decentralized grouping includes: identifying, by each node of a plurality of nodes in a blockchain network that manages a blockchain, a plurality of groups, where each is comprised of a subset of nodes; generating, by each node in each subset of nodes, a new block for the blockchain; performing, by each subset of nodes, a first consensus operation among all nodes in the subset of nodes for the new block generated by in the subset of nodes to identify a group consensus block, where each node in the subset of nodes receives the group's group consensus block; and performing, by the blockchain network, a second consensus operation among all groups for the identified group consensus block to identify an overall consensus block, where a majority of groups of the plurality of groups receives the overall consensus block.

Abstract: Systems and methods are described for processing records associated with a query that identifies an association between two data fields. The system can obtain a chunk of data that includes multiple records based on a query received by a data intake and query system. At least one record can include multiple sub-records that share a field value for at least one field. The system can generate a record from each sub-record and assign the generated records to one or more groups of partitions. The system can combine record data of generated records assigned to one partition of a group of partitions and then combine record data across the group of partitions. The system can process the results of the combination of records across the group of partitions based on the query.

Abstract: A microservice or serverless process consistency check process comprising locating all the necessary metadata and data objects in the cloud by storing the data objects in the cloud and synchronously mirroring the metadata, which is separately stored in local storage, to the cloud. The process generates a list of data objects in the cloud as “Set A” and the list of metadata objects in the same prefix range as the data objects as “Set B.” The consistency check then verifies whether all objects in Set A are referred to by objects in set B. In the case where there are gaps between the sets, non-existent objects are marked as missing, and unreferenced objects are marked as orphan objects. The list of missing and orphan objects is then sent back to the backup server for analysis and further processing.

Abstract: Advanced resource selection is disclosed. A request from a client to resolve an augmented domain is received at a Domain Name System (DNS) server. Information is extracted from the augmented domain name. The extracted information is used to select a particular resource from a set of resources to provide content to the client.

Abstract: A storage array uses paged metadata. Each storage director has access to a plurality of object storage systems which describe locations of paged metadata in backing storage. Each object storage system includes different types of inodes which describe objects in backing storage. The object storage systems are used to locate and relocate metadata for loading into global memory, and creation and deletion of objects. An object storage system may be selected based on factors including ratio of different inode types, locality of object usage and anticipated object activity level.

Abstract: Systems and methods are provided for generating reports reflecting a visualization of, e.g., a dataset on which data analysis has been performed. The data analysis performed on the dataset may be an aggregation of data analysis functionality provided by applications or tools. Dataset visualization is realized in a workspace implemented by a separate application or tool. Potential conflicts regarding updating one or more elements of the dataset are reconciled by implementing a dual operational transform system and method. A global state of the dataset may be determined by a first operational transform system and method, while a local state of the dataset may be determined by a second operational transform system and method. The local state of the dataset may be updated through operational transforms exchanged between the first and second operational transform systems that align the local state of the dataset with the global state of the dataset.

Abstract: The disclosed embodiments also include monitoring and metering services of the data fabric service (DFS) system. Specifically, these services can include techniques for monitoring and metering metrics of the DFS system. The metrics are standards for measuring use or misuse of the DFS system. Examples of the metrics include data or components of the DFS system. For example, a metric can include data stored or communicated by the DFS system or components of the DFS system that are used or reserved for exclusive use by customers. The metrics can be measured with respect to time or computing resources (e.g., CPU utilization, memory usage) of the DFS system. For example, a DFS service can include metering the usage of particular worker nodes by a customer over a threshold period of time.